Systems and methods for automatically characterizing disturbances in an electrical system

Abstract

A method for automatically categorizing disturbances in an electrical system includes capturing at least one energy-related waveform using at least one intelligent electronic device in the electrical system, and processing electrical measurement data from, or derived from, the at least one energy-related waveform to identify disturbances in the electrical system. In response to identifying a disturbance in the electrical system, each sample of the at least one energy-related waveform associated with the identified disturbance is analyzed and categorized into one of a plurality of disturbance categories. The disturbance categories may include, for example, (a) voltage sags due to upline electrical system disturbances, (b) voltage sags due to downline electrical system faults, (c) voltage sags due to downline transformer and/or motor magnetization, and (d) voltage sags due to other downline disturbances.

1 . A method for automatically categorizing disturbances in an electrical system, comprising:
 processing electrical measurement data from, or derived from, at least one energy-related waveform captured by at least one intelligent electronic device (IED) in the electrical system to identify disturbances in the electrical system to identify disturbances in the electrical system;   in response to identifying the disturbances in the electrical system, analyzing and categorizing samples of the at least one energy-related waveform associated with the identified disturbances into one of a plurality of disturbance categories, the disturbance categories including: (a) voltage sags due to upline electrical disturbances, (b) voltage sags due to downline electrical system faults, (c) voltage sags due to downline transformer and/or motor magnetization, and (d) voltage sags due to other downline disturbances; and   determining a disturbance categorization for the at least one energy-related waveform associated with the identified disturbances based on the categorization of the samples of the at least one energy-related waveform, the disturbance categorization being selected from one of the disturbance categories.   
     
     
         2 . The method of  claim 1 , wherein the at least one energy-related waveform includes at least one of: voltage waveforms, current waveforms, and other waveforms and/or data derived from the voltage waveforms and/or the current waveforms. 
     
     
         3 . The method of  claim 1 , wherein processing electrical measurement data from, or derived from, the at least one energy-related waveform to identify disturbances in the electrical system, includes:
 determining voltage and current phase information of the electrical measurement data associated with the disturbances, and analyzing the voltage and current phase information to determine if the source(s) of the disturbances is/are electrically upstream or downstream from electrical nodes or locations in the electrical system where the at least one IED is electrically coupled; or   grouping the electrical measurement data based on electrical nodes or locations in the electrical system associated with the at least one energy-related waveform, and processing the grouped electrical measurement data to identify disturbances at the electrical nodes or locations.   
     
     
         4 . The method of  claim 1 , wherein determining a disturbance categorization for the at least one energy-related waveform, includes: analyzing the categorization of the samples of the at least one energy-related waveform to develop a confidence factor on a disturbance categorization for the at least one energy-related waveform, and in response to the confidence factor of the disturbance characterization meeting a threshold, determining the disturbance categorization for the at least one energy-related waveform. 
     
     
         5 . The method of  claim 4 , wherein analyzing the categorization of the samples of the energy-related waveforms includes identifying categorization patterns of the energy-related waveform samples. 
     
     
         6 . The method of  claim 1 , further comprising: taking at least one action based on the disturbance categorization for the at least one energy-related waveform. 
     
     
         7 . The method of  claim 6 , wherein taking one or more actions based on the disturbance categorization includes triggering one or more alarms based on the disturbance categorization. 
     
     
         8 . The method of  claim 7 , wherein the alarms are prioritized based on importance/criticality of electrical node or location where the disturbance originated, or based on size of the load measured at the electrical node or location where the disturbance. 
     
     
         9 . The method of  claim 6 , wherein the one or more actions are automatically performed by a control system associated with the electrical system, wherein the control system is communicatively coupled to the at least one IED, and/or to a cloud-based system, on-site/edge software, a gateway, and another head-end system associated with the electrical system. 
     
     
         10 . The method of  claim 9 , wherein the electrical measurement data from, or derived from, the at least one energy-related waveform captured by the at least one IED is processed on at least one of: the cloud-based system, the on-site software, the gateway, and the other head-end system associated with the electrical system, wherein the at least one IED is communicatively coupled to the at least one of: the cloud-based system, the on-site software, the gateway, and the other head-end system on which the electrical measurement data is processed. 
     
     
         11 . The method of  claim 1 , wherein the disturbances are identified based on at least a duration of a detected event from the electrical measurement data. 
     
     
         12 . The method of  claim 1 , wherein one or more missing channels from the measurement data are estimated. 
     
     
         13 . A system for automatically categorizing disturbances in an electrical system, comprising:
 a processor;   a memory device; and   one or more processors, in communication with the memory device, configured to:
 process electrical measurement data from, or derived from, at least one energy-related waveform captured by at least one intelligent electronic device (IED) in the electrical system to identify disturbances in the electrical system; 
   in response to identifying the disturbances in the electrical system, analyze and categorize samples of the at least one energy-related waveform associated with the identified disturbances into one of a plurality of disturbance categories, the disturbance categories including: (a) voltage sags due to upline electrical disturbances, (b) voltage sags due to downline electrical system faults, (c) voltage sags due to downline transformer and/or motor magnetization, and (d) voltage sags due to other downline disturbances; and   determine a disturbance categorization for the at least one energy-related waveform associated with the identified disturbances based on the categorization of the samples of the at least one energy-related waveform, the disturbance categorization being selected from one of the disturbance categories.   
     
     
         14 . The system of  claim 13 , wherein the at least one energy-related waveform includes at least one of: voltage waveforms, current waveforms, and other waveforms and/or data derived from the voltage waveforms and/or the current waveforms. 
     
     
         15 . The system of  claim 13 , wherein the disturbances are identified by grouping the electrical measurement data based on electrical nodes or locations in the electrical system associated with the at least one energy-related waveform, and processing the grouped electrical measurement data to identify the disturbances at the electrical nodes or locations. 
     
     
         16 . The system of  claim 13 , wherein the disturbance categorization for the at least one energy-related waveform is determined by analyzing the categorization of the samples of the at least one energy-related waveform to develop a confidence factor on a disturbance categorization for the at least one energy-related waveform, and in response to the confidence factor of the disturbance characterization meeting a threshold, determining the disturbance categorization for the at least one energy-related waveform. 
     
     
         17 . The system of  claim 13 , wherein the one or more processors are further configured to take at least one action based on the disturbance categorization for the at least one energy-related waveform. 
     
     
         18 . The system of  claim 17 , wherein the one or more actions include:
 triggering one or more alarms based on the disturbance categorization; or   generating an output signal in accordance with the disturbance categorization, and providing the output signal to at least one device for further processing.   
     
     
         19 . A non-transitory computer medium storing computer executable code, which when executed by one or more processors, is configured to implement a method of automatically categorizing disturbances in an electrical system, the method comprising:
 processing electrical measurement data from, or derived from, at least one energy-related waveform captured by at least one intelligent electronic device (IED) in the electrical system to identify disturbances in the electrical system to identify disturbances in the electrical system;   in response to identifying the disturbances in the electrical system, analyzing and categorizing samples of the at least one energy-related waveform associated with the identified disturbances into one of a plurality of disturbance categories, the disturbance categories including: (a) voltage sags due to upline electrical disturbances, (b) voltage sags due to downline electrical system faults, (c) voltage sags due to downline transformer and/or motor magnetization, and (d) voltage sags due to other downline disturbances; and   determining a disturbance categorization for the at least one energy-related waveform associated with the identified disturbances based on the categorization of the samples of the at least one energy-related waveform, the disturbance categorization being selected from one of the disturbance categories.   
     
     
         20 . The non-transitory computer medium of  claim 19 , wherein the method further comprises taking at least one action based on the disturbance categorization for the at least one energy-related waveform.